Presents cases and examples of collective and computational intelligence applications in the energy industry

Includes collective and computational intelligence techniques such as ant colony optimization, swarm optimization, simulated annealing, genetic algorithms, neural networks, fuzzy sets 

Gives insights for investigation and projection of energy plans and schedules using the most recent analytical methods classified in collective and computational intelligence